4 citations · 5 across the 3 of their papers we have counts for
3 papers
eess.IV2022
Undersampled MRI Reconstruction with Side Information-Guided Normalisation
Xinwen Liu, Jing Wang, Cheng Peng +3
Magnetic resonance (MR) images exhibit various contrasts and appearances based on factors such as different acquisition protocols, views, manufacturers, scanning parameters, etc. T…
cs.CV2021★ 4 cited
Deep Simultaneous Optimisation of Sampling and Reconstruction for Multi-contrast MRI
Xinwen Liu, Jing Wang, Fangfang Tang +3
MRI images of the same subject in different contrasts contain shared information, such as the anatomical structure. Utilizing the redundant information amongst the contrasts to sub…
cs.CV2021★ 1 cited
Universal Undersampled MRI Reconstruction
Xinwen Liu, Jing Wang, Feng Liu +1
Deep neural networks have been extensively studied for undersampled MRI reconstruction. While achieving state-of-the-art performance, they are trained and deployed specifically for…